Design and implementation of large-scale maritime simulation engine in the context of big data

Large-scale maritime simulation platform faces the contradiction among timeliness, accuracy and integrity in the data collection, storage, analysis and exploitation, due to the features of maritime big data, such as large-volume, multi-source heterogeneity, abruptness and high noise. With this background, in order to deal with the complexity and imperfectness of maritime big data, this paper employs the networked data as the analysis object with more emphasis on the indirect relevance and in-depth analysis. By analyzing the modeling system of maritime simulation platform based on BOM (Base Object Model), designs a Large-scale Maritime Simulation Frame (LMSF). Simultaneously, to solve the problems such as the low efficiency and the high cost due to the difficulty in heterogeneous model integration and the inadequate reuse rate of components, we implement the prototype system of large-scale maritime simulation platform based on HLA (High Level Architecture). In this way, the paper presents a package solution for multitasking interactive operation by multiple people of multiple roles. This paper also introduces how to verify the proposed LMSF on the newly developed maritime emergency simulation platforms with some typical maritime accident and human-in-the-loop test. With numerous tests, the proposed LMSF shows a good adaptation to the collection, storage, analysis and exploitation of maritime big data, more important, it has good scalability and high performance.